| AVEC 2019 workshop and challenge: state-of-mind, detecting depression with AI, and cross-cultural affect recognition F Ringeval, B Schuller, M Valstar, N Cummins, R Cowie, L Tavabi, ... Proceedings of the 9th International on Audio/visual Emotion Challenge and …, 2019 | 346 | 2019 |
| Exploring temporal representations by leveraging attention-based bidirectional LSTM-RNNs for multi-modal emotion recognition C Li, Z Bao, L Li, Z Zhao Information Processing & Management 57 (3), 102185, 2020 | 197 | 2020 |
| Exploring deep spectrum representations via attention-based recurrent and convolutional neural networks for speech emotion recognition Z Zhao, Z Bao, Y Zhao, Z Zhang, N Cummins, Z Ren, B Schuller IEEE access 7, 97515-97525, 2019 | 130 | 2019 |
| A multiple mobile robots path planning algorithm based on A-star and Dijkstra algorithm Z Zhang, Z Zhao International Journal of Smart Home 8 (3), 75-86, 2014 | 121 | 2014 |
| Combining a parallel 2D CNN with a self-attention Dilated Residual Network for CTC-based discrete speech emotion recognition Z Zhao, Q Li, Z Zhang, N Cummins, H Wang, J Tao, BW Schuller Neural Networks 141, 52-60, 2021 | 98 | 2021 |
| Automatic assessment of depression from speech via a hierarchical attention transfer network and attention autoencoders Z Zhao, Z Bao, Z Zhang, J Deng, N Cummins, H Wang, J Tao, B Schuller IEEE Journal of Selected Topics in Signal Processing 14 (2), 423-434, 2019 | 89 | 2019 |
| Exploring spatio-temporal representations by integrating attention-based bidirectional-LSTM-RNNs and FCNs for speech emotion recognition Z Zhao, Y Zheng, Z Zhang, H Wang, Y Zhao, C Li | 89 | 2018 |
| Attention-enhanced connectionist temporal classification for discrete speech emotion recognition Z Zhao, Z Bao, Z Zhang, N Cummins, H Wang, B Schuller | 77 | 2019 |
| A hierarchical attention network-based approach for depression detection from transcribed clinical interviews A Mallol-Ragolta, Z Zhao, L Stappen, N Cummins, B Schuller | 66 | 2019 |
| End-to-end automatic pronunciation error detection based on improved hybrid ctc/attention architecture L Zhang, Z Zhao, C Ma, L Shan, H Sun, L Jiang, S Deng, C Gao Sensors 20 (7), 1809, 2020 | 62 | 2020 |
| Deep spectrum feature representations for speech emotion recognition Z Zhao, Y Zhao, Z Bao, H Wang, Z Zhang, C Li Proceedings of the Joint Workshop of the 4th Workshop on Affective Social …, 2018 | 59 | 2018 |
| Classification of lung nodules based on deep residual networks and migration learning P Wu, X Sun, Z Zhao, H Wang, S Pan, B Schuller Computational intelligence and neuroscience 2020 (1), 8975078, 2020 | 58 | 2020 |
| Hierarchical attention transfer networks for depression assessment from speech Z Zhao, Z Bao, Z Zhang, N Cummins, H Wang, B Schuller ICASSP 2020-2020 IEEE international conference on acoustics, speech and …, 2020 | 55 | 2020 |
| Hybrid network feature extraction for depression assessment from speech Z Zhao, Q Li, N Cummins, B Liu, H Wang, J Tao, B Schuller | 48 | 2020 |
| Audiovisual analysis for recognising frustration during game-play: introducing the multimodal game frustration database M Song, Z Yang, A Baird, E Parada-Cabaleiro, Z Zhang, Z Zhao, ... 2019 8th International conference on affective computing and intelligent …, 2019 | 35 | 2019 |
| Hierarchical attention-based temporal convolutional networks for eeg-based emotion recognition C Li, B Chen, Z Zhao, N Cummins, BW Schuller ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 33 | 2021 |
| Self-attention transfer networks for speech emotion recognition Z Zhao, K Wang, Z Bao, Z Zhang, N Cummins, S Sun, H Wang, J Tao, ... Virtual Reality & Intelligent Hardware 3 (1), 43-54, 2021 | 30 | 2021 |
| Predicting the epidemics trend of COVID-19 using epidemiological-based generative adversarial networks H Wang, G Tao, J Ma, S Jia, L Chi, H Yang, Z Zhao, J Tao IEEE Journal of Selected Topics in Signal Processing 16 (2), 276-288, 2022 | 28 | 2022 |
| Deep learning for mobile mental health: Challenges and recent advances J Han, Z Zhang, C Mascolo, E André, J Tao, Z Zhao, BW Schuller IEEE Signal Processing Magazine 38 (6), 96-105, 2021 | 28 | 2021 |
| Autism screening using deep embedding representation H Wang, L Li, L Chi, Z Zhao Computational Science–ICCS 2019: 19th International Conference, Faro …, 2019 | 28 | 2019 |
Björn SchullerProfessor, Technische Universität München (TUM) / Imperial College London & CSO, audEERINGVerified email at tum.de
